Sustainable procurement of water supply infrastructure projects: a building information modeling-based approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Triple Bottom Line (TBL)-based project proposal evaluation is highly data-intensive. The above challenge is elevated when considering the complex nature of construction projects. Emerging concepts, such as Building Information Modeling (BIM), provide a data repository that aids TBL-based proposal evaluation. Despite national-level BIM mandates, there is a lack of BIM-based TBL performance evaluation tools. Hence, this study developed a BIM plugin toolkit to automate proposal evaluation of water supply infrastructure projects by considering the TBL performance. This toolkit incorporates a unique TBL-based evaluation methodology that integrates environmental product declarations, social life cycle impact, and life cycle costing. The case study revealed that the selected proposal had superior environmental and social performance while the bid price was slightly higher (6.5%) than the lowest-cost proposal. The proposed method provides a user-friendly tool for TBL-based proposal evaluation and promotes BIM implementation in the construction industry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it